import tempfile
import unittest

from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
from transformers.testing_utils import (
    is_torch_available,
    require_optimum,
    require_torch,
    slow,
)


if is_torch_available():
 import torch

@require_torch
@require_optimum
@slow
class 					_lowercase    (     unittest.TestCase			):






    '''simple docstring'''




    def      _a    (    self ):
       lowerCAmelCase_:							List[Any]       =	"hf-internal-testing/tiny-random-t5"
       lowerCAmelCase_:							List[str]       =	AutoTokenizer.from_pretrained(lowerCamelCase__ )
       lowerCAmelCase_:							List[str]       =	AutoModelForSeqaSeqLM.from_pretrained(lowerCamelCase__ )

       lowerCAmelCase_:							Optional[int]       =	tokenizer("This is me"       ,						return_tensors="pt" )

       lowerCAmelCase_:							Tuple       =	model.to_bettertransformer()

       self.assertTrue(any("BetterTransformer" in mod.__class__.__name__ for _, mod in model.named_modules() ) )

       lowerCAmelCase_:							Any       =	model.generate(**lowerCamelCase__ )

       lowerCAmelCase_:							List[Any]       =	model.reverse_bettertransformer()

       self.assertFalse(any("BetterTransformer" in mod.__class__.__name__ for _, mod in model.named_modules() ) )

       with tempfile.TemporaryDirectory() as tmpdirname:
          model.save_pretrained(lowerCamelCase__ )

          lowerCAmelCase_:							str       =	AutoModelForSeqaSeqLM.from_pretrained(lowerCamelCase__ )

          self.assertFalse(
              any("BetterTransformer" in mod.__class__.__name__ for _, mod in model_reloaded.named_modules() ) )

          lowerCAmelCase_:							Optional[int]       =	model_reloaded.generate(**lowerCamelCase__ )
          self.assertTrue(torch.allclose(lowerCamelCase__       ,						lowerCamelCase__ ) )




    def      _a    (    self ):
       lowerCAmelCase_:							int       =	"hf-internal-testing/tiny-random-t5"
       lowerCAmelCase_:							List[str]       =	AutoModelForSeqaSeqLM.from_pretrained(lowerCamelCase__ )

       lowerCAmelCase_:							int       =	model.to_bettertransformer()

       with tempfile.TemporaryDirectory() as tmpdirname:
          with self.assertRaises(lowerCamelCase__ ):
             model.save_pretrained(lowerCamelCase__ )

          lowerCAmelCase_:							Optional[Any]       =	model.reverse_bettertransformer()
          model.save_pretrained(lowerCamelCase__ )
"""simple docstring"""



def 	_lowerCamelCase(	a				):
       return " ".join(
           "".join(word[::-1]				) if len(a				) > 4 else word for word in sentence.split()				)


if __name__ == "__main__":
   import doctest

   doctest.testmod()
   print(reverse_long_words("""Hey wollef sroirraw"""))
